Data Platform Engineer, Digital Operations

At BETA Technologies, we apply our intellectual curiosity, passion for aviation, and commitment to sustainability toward a shared mission of revolutionizing electric aviation. Regardless of the position one holds, each team member brings their talent and desire to positively impact the environment and lives of others in a refreshing, vibrant, and inclusive culture.

We are seeking a bringing strong hands-on engineering skills and a builder's mindset to help design, deploy, and operate the data and knowledge infrastructure that powers our organization. In this role, you will combine software and data engineering fundamentals with practical experience in cloud-native architectures, graph databases, and API design to build robust, scalable production systems that enable rich data discovery, seamless integration, and reliable access across diverse data sources. You will work collaboratively with data scientists, other platform engineers, and domain experts to evaluate, architect, and implement the most appropriate data solutions, and then roll up your sleeves to build, deploy, and maintain them in production. The ideal candidate is a pragmatic, hands-on technologist who thrives on solving real infrastructure and data challenges end-to-end, from initial design through production operations, and who takes pride in building systems that make data more findable, accessible, and reusable across the enterprise.

How you will contribute to revolutionizing electric aviation:

• Design, build, and operate scalable data platform services and frameworks that empower domain teams to manage their data assets within a cohesive enterprise architecture

• Implement data integration solutions that create a digital thread connecting information across the entire product lifecycle from design through manufacturing to field operations

• Build and maintain data storage systems including data lakes, warehouses, and graph databases that make organizational data accessible and ready to power advanced analytics and AI

• Create and extend enterprise data catalog capabilities that document what data exists across organizational systems, how it is structured, and how it connects, enabling teams across the company to navigate the full data landscape

• Develop and expose performant data access layers using technologies such as GraphQL and REST APIs, providing intuitive interfaces to complex underlying data

• Deploy, monitor, and manage production data systems on cloud infrastructure, ensuring high availability, performance, and reliability

• Implement data quality and lineage solutions that ensure accuracy and traceability across diverse data types; essential for aerospace compliance and establishing a trusted foundation for analytics and AI

• Build and maintain CI/CD pipelines, infrastructure as code, and automated deployment processes that keep our data platform agile, reproducible, and production-ready